Issue #98
April 11, 2021
- 1. Why Causal Machine Learning is the Next Revolution in AI [medium.com/@ODSC]
- 2. Using PyTorch + NumPy? You're making a mistake [tanelp.github.io]
- 3. Announcing the Neo4j GraphQL Library Beta Release [medium.com/neo4j]
- 4. Confronting 2016 and 2020 Polling Limitations [pewresearch.org]
- 5. 10 Parallels Between Whiskey Tasting and Artificial Intelligence [cio.com]
- 6. On the future of computer science [xrds.acm.org]
- 7. Writing tools I learned from The Economist [builtbywords.substack.com]
- 8. NoSQL Data Modeling Techniques [highlyscalable.wordpress.com]
- 9. A reading list for new engineering managers [jacobian.org]
- 10. Are Deep Neural Networks Dramatically Overfitted? [lilianweng.github.io]
- 11. Mathematicians Settle Erdős Coloring Conjecture [quantamagazine.org]
- 12. Learning COBOL: A Journey for the Modern Programmer [monadical.com]
- • Measuring voluntary and policy-induced social distancing behavior during the COVID-19 pandemic (Y. Yan, A. A. Malik, J. Bayham, E. P. Fenichel, C. Couzens, S. B. Omer)
- • Time to regulate AI that interprets human emotions (K. Crawford)
- • Causal Interpretations of Black-Box Models (Q. Zhao, T. Hastie)
- • The Matrix Calculus You Need For Deep Learning (T. Parr, J. Howard)
- • A Bayesian Approach to the Simulation Argument (D. Kipping)
- • Ten simple rules to colorize biological data visualization (J. A. Pouwelse)
- • Scaling Scaling Laws with Board Games (A. L. Jones)
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